Abstract:
:In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.
journal_name
BMB Repjournal_title
BMB reportsauthors
Paik H,Ryu T,Heo HS,Seo SW,Lee D,Hur CGdoi
10.5483/BMBRep.2011.44.4.250subject
Has Abstractpub_date
2011-04-01 00:00:00pages
250-5issue
4eissn
1976-6696issn
1976-670Xjournal_volume
44pub_type
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